Pre-or co-SARS-CoV-2 Infections Significantly Increase Severe Dengue Virus Disease Criteria: Implications for Clinicians

Few studies have investigated whether SARS-CoV-2 infections increase the incidence of dengue haemorrhagic fever/shock syndrome (DHF/DSS) and/or severe dengue (SD) in dengue virus (DENV)-infected patients. This study was performed on a site with high incidences of classical dengue, but relatively few DHF/DSS or SD cases as defined by the WHO 1997 or 2009 criteria, respectively. Clinical, haematological/biochemical, and viral diagnostic data were collected from febrile patients before, during, and after the COVID-19 epidemic to assess whether (a) DENV-infected patients with prior SARS-CoV-2 infections or (b) DENV-SARS-CoV-2-co-infected patients had increased incidences of SD/DHF/DSS using logistic regression and machine learning models. Higher numbers of DHF/DSS/SD occurred during the COVID-19 epidemic, particularly in males and 18–40-year-olds. Significantly increased symptoms in the DENV-SARS-CoV-2-co-infected cases were (a) haemoconcentration (p < 0.0009) and hypotension (p < 0.0005) (DHF/DSS and SD criteria), (b) thrombocytopenia and mucosal bleeding (DHF/DSS-criteria), (c) abdominal pain, persistent vomiting, mucosal bleeding, and thrombocytopenia (SD warning signs) and (d) dyspnoea, but without fluid accumulation. DENV-infected patients with prior SARS-CoV-2 infections had significantly increased incidences of thrombocytopenia (DHF/DSS-criteria) and/or abdominal pain and persistent vomiting and also thrombocytopenia (SD warning signs), but without significant haemoconcentration or hypotension. DENV-SARS-CoV-2 co-infections significantly increased the incidence of DHF/DSS/SD, while DENV-infected patients with prior SARS-CoV-2 infections displayed significantly increased incidences of thrombocytopenia (DHF/DSS-criteria) and three important SD warning signs, which are therefore very important for health workers/clinicians in assessing patients’ DHF/DSS/SD risk factors and planning their optimal therapies.


Introduction
Dengue virus (DENV), with four discrete serotypes, has become endemic in most tropical and subtropical countries of the world and globally causes an estimated 100-400 million cases of infections annually [1].Dengue fever (DF) usually occurs as a self-limiting febrile disease, termed classical DF; however, it can also be associated with severe life-threatening manifestations like dengue haemorrhagic fever and shock syndrome (DHF/DSS).The clinical diagnostic criteria for DHF and DSS have been fully defined by the World Health Organization [2] and have been used as the reference criteria for distinguishing between DF, DHF, and DSS cases.As such, the hallmark for DF and DHF discrimination has been: (a) vascular leakage leading to haemoconcentration through >20% increased haematocrit values above the average for age, sex, and population and fluid accumulation as observed by pleural effusion, ascites, or hypo-proteinuria, (b) increased bleeding through a range of symptoms including a positive tourniquet test, petechiae, purpura, mucosal or injection-site bleeding, or haematemesis/melena, (c) severe thrombocytopenia (<100,000/µL), and, often, (d) hepatomegaly (>2 cm) [2].DHF cases were further subdivided into four grades (DHF I to IV), where DHF III and IV were further classified by narrowed (<20 mm Hg) pulse pressure or hypotension (DHF III) or profound shock (DHF IV).
Subsequently, the WHO altered the definition of DHF/DSS to 'severe dengue' (SD), which also included SD warning signs [3].The latter was introduced to include the range of different organ diseases associated with DENV infections and other results resulting from vascular leakage fluid accumulations, such as acute respiratory distress syndrome (ARDS).Although generally accepted, these new SD classifications based on severe vascular leakage, bleeding, and organ damage (including encephalopathy) and SD warning signs have also been criticised due to not including established discriminatory values for thrombocytopenia, elevation of haemoconcentration (haematocrit), or pulse pressures as was provided in the WHO 1997 criteria [4,5], while an early meta-analysis claimed that the WHO 2009 criteria were more reliable for identifying severe cases [6].In other studies, however, (a) both the WHO 1997 and 2009 criteria were equally effective, but the WHO 2009 criteria were also better for the identification of the most severe cases [7]; (b) the WHO 1997 criteria for plasma leakage and hemodynamic compromise was suggested to be re-introduced into the WHO 2009 SD criteria [5]; and (c) the WHO 2019 criteria had a low sensitivity for patients requiring urgent care and predicting mortality, and the authors strongly suggested that thrombocytopenia-related bleeding should be re-introduced into the WHO 2009 SD criteria, together with the effects of particular chronic diseases [8].As such, it is therefore prudent to employ both the WHO 1997 and 2009 DHF/DSS/SD criteria for application to DENV-infected patients to subsequently identify and employ the appropriate therapies for all life-threatening DENV cases.
The COVID-19 pandemic, caused by SARS-CoV-2, led to more than 768 million infections and 7 million deaths throughout the world, and caused a large number of deaths due to acute and chronic disease (long COVID-19) in patients [9].Further, acute disease was associated with acute respiratory distress and hypoxia; many of the symptoms of SARS-CoV-2 infections are similar to those displayed by classical DF patients [9,10], thereby making clinical differential diagnosis difficult, but while acute dyspnoea (ARDS: acute respiratory distress syndrome) often occurs in symptomatic acute SARS-CoV-2 cases, it may also lead to chronic pulmonary disease as well as multi-organ disease symptoms in 'long-COVID' cases [11].Despite the expected high incidence of DENV-SARS-CoV-2 co-infections in DENV endemic areas, only a few studies have been performed on their outcomes [12,13].To the best of our knowledge, there have been no studies performed to also assess whether the DENV-infected patients who were previously infected with SARS-CoV-2 infections displayed significantly increased incidences of WHO 1997 DHF/DSS or WHO 2009 SD and SD warning sign criteria despite their importance for health workers.
Barranquilla is a principal seaport on the Caribbean coast of Colombia where all four DENV serotypes are endemic and cause large numbers of self-limiting DF throughout the year, but where DHF/DSS/SD cases are rare [14,15].As such, this study site was an ideal location to investigate whether the COVID-19 epidemic increased the incidence of DENV disease when assessed using both the WHO 1997 DHF/DSS-defined criteria and the WHO 2009 SD and SD warning sign criteria in DENV-SARS-CoV-2-co-infected patients or, very importantly and uniquely, also in DENV-infected patients who had previously encountered SARS-CoV-2 infections.

Setting and Population
Febrile patients were recruited from hospitals in the Caribbean coastal city of Barranquilla, Colombia, between 2018 and 2022 and were only included in this study if they were then confirmed as anti-dengue virus (DENV) IgM ELISA-positive for dengue virus and also had a high (>38 • C) fever and at least one of these clinical symptoms: (i) retro-orbital pain, (ii) myalgia, (iii) headache, or (iv) rash.Patients with suspected SARS-CoV-2 infections (COVID-19 disease) were confirmed using a specific reverse-transcription polymerase chain reaction (RT-PCR).
The DENV-infected cases were then assessed for symptoms of serious disease using the combined WHO 1997 dengue haemorrhagic fever/dengue shock syndrome (DHF/DSS) criteria [2] and the updated WHO 2009 severe dengue (SD) with SD warning signs [3] Patient (demographic and clinical) information was registered by each of the hospitals in a case report form for dengue and SARS-CoV-2 infections as part of the national surveillance system for public health (SIVIGILA).For this study, we reviewed the medical records of all DENV-infection-confirmed cases that occurred before, during and after the COVID-19 epidemic in Barranquilla to investigate whether SARS-CoV-2 infections resulted in significantly increased incidences of DHF/DSS/SD cases, based on the WHO DHF/DSS 1997 and WHO SD and SD warning sign criteria due to DENV-SARS-CoV-2 co-infections or in DENV-infected cases who had previously encountered SARS-CoV-2 infections.

Statistical Analysis
In the descriptive analysis, frequencies, and percentages (%) were used to present the qualitative variables.The chi-square test and Fisher exact test were performed to compare the percentages between the co-infected and non-co-infected cases, between SARS-CoV-2 positive and negative cases, and between severe (DHF/DSS/SD) and non-severe dengue cases, as appropriate.
Logistic regression analysis was first performed to identify the more important clinical manifestations and laboratory findings associated with co-infected patients, and second the clinical symptoms that influenced DENV infection severity in patients.In multivariate analysis, the co-infected model was further analysed by adding the clinical manifestations and laboratory finding variables simultaneously and eliminating the less significant variables (i.e., p > 0.05) from the model and the final model retained only significant variables.As age has a crucial role in infectious diseases, we integrated age into the final model.Further, multivariate analyses were conducted to compare symptomatic patterns between DENV-infected patients with previous SARS-CoV-2 infection history.The fitness of models was evaluated using the Bayesian Information Criterion (BIC) and the variance inflation factor (VIF) was used to evaluate multicollinearity in the models.Further, odds ratios (crude odds ratios (crude ORs) and adjusted odds ratios (aORs)) were estimated with 95% confidence intervals (95% CIs) to quantify the associations between independent factors with diseases in all models.
Machine learning techniques including decision tree (DT) and random forest (RF) models were utilised to find the key risk factors for DHF/DSS/SD (severe dengue) patients.
By using random assignment, we conducted a split-sample validation and a facilitation model was constructed using a training sample (80%) that was tested on a hold-out sample (20%).We set the parent node to 30 and the child node to 10 for the minimum number of cases.Furthermore, we pruned the tree to avoid overfitting.The result's validity indicated the unbiased assessment of fitted models using training datasets.Thus, the index including positive predictive value, negative predictive value, sensitivity, specificity, accuracy and AUC were used to validate the models.
Based on the selected model, we computed the feature importance on permuted out-ofbag (OOB) samples for DHF/DSS/SD (severe dengue) patients by using the mean decrease accuracy method.The higher mean decreased accuracy indicated the more important features.All analyses were performed in the R language software (version 4.4.0)[16].The R package CARET [17] was used for logistic regression models and RF and RPART [18] for DT.

Important Features of DHF/DSS/SD Cases
The most important factors for DHF/DSS/SD were age, dyspnoea, reduced platelets, SARS-CoV-2 co-infection, and haemoconcentration (Figure 1).The statistical results of machine learning techniques indicated that the RF model performed better than the DT model in both the training and testing stages.The accuracy and AUC values for RF and DT are assessed as (0.85, 0.90) and (0.80, 0.86), respectively (Table S6).Moreover, after adjusting the multivariate logistic model for DHF/DSS/SD, the model identified the nine independent indicators for DHF/DSS/SD as fever, headache, retro-orbital pain, myalgia, arthralgia, abdominal pain, dyspnoea, haemoconcentration, previous SARS-CoV-2 infection and reduced platelet numbers (thrombocytopenia) (Table 4).

Discussion
The main findings of this study were firstly that DENV-SARS-CoV-2 co-infections resulted in a significantly increased incidence of DHF/DSS/SD cases based on both the WHO 1997 DHF/DSS and the WHO 2009 SD with SD warning signs criteria in an area where severe DENV disease is relatively rare.Importantly, the most salient discriminatory criterion in both guidelines is vascular leakage, which was evident due to the significantly increased incidence of haemoconcentration (DHF/SD criteria), which also led to a significantly increased incidence of hypotension (DSS/SD criteria) in these DENV-SARS-CoV-2-co-infected patients.These results are, therefore, in agreement with those published previously [12,13].Secondly, previous SARS-CoV-2 infections were also associated with a significantly increased incidence of thrombocytopenia and mucosal bleeding using the WHO 1997 DHF/DSS criteria, while they displayed significant incidences of important SD warning signs of abdominal pain, persistent vomiting, and reduced platelet numbers (thrombocytopenia).As such, we believe that this is the first report of the WHO 1997 or WHO 2009 DHF/DSS/SD or SD warning signs criteria being assessed and shown to be significantly increased in DENV-infected patients due to previous SARS-CoV-2 infections.The results strongly suggest that health workers need to question DENV-infected patients as to whether they have previously encountered confirmed or suspected SARS-CoV-2 infections due to these findings and to re-introduce thrombocytopenia and other known risks due to particular chronic diseases into the WHO SD criteria, as was suggested previously [8].While a significantly increased incidence of dyspnoea/ARDS was identified in the DENV-SARS-CoV-2-co-infected patients, it is common in symptomatic SARS-CoV-2 patients but is also a WHO 2009 SD warning sign.The lack of significant fluid accumulation despite the significantly increased incidence of abdominal pain in the DENV-SARS-CoV-2-co-infected patients, however, suggested that the dyspnoea/ARDS incidence was mainly due to their SARS-CoV-2 infection.Dyspnoea/ARDS was not, however, significantly increased in the DENV-infected patients who had encountered previous SARS-CoV-2 infections.It would, therefore, be very interesting to establish whether patients with multi-organ symptoms, including pulmonary disease, due to chronic 'long-COVID' [11] have statistically increased incidence of DHF/DSS/SD disease or other SD warning signs and should, therefore, also be assessed in further studies.
There was a higher incidence of DENV infections as well as DENV-SARS-CoV-2-coinfected cases in patients from the lower (1-4) socio-economic strata than patients from strata 5 and 6, which was likely to be due to residents residing in houses rather than apartments, which increased the risk of reported DENV infections [19,20].This is especially due to higher numbers of large-volume domestic water-storage containers [21], which are the principal breeding sites for its vector species, Aedes aegypti [14].As such, the Barranquilla Health Authorities have consistently reported that neighbourhoods within these lower economic strata have much higher incidences of human DENV infections through their efficient national guidelines [22] and have, therefore, been the focus of surveillance and control efforts in this city [23,24] and elsewhere in Colombia [23,25].Patients with DHF/DSS/SD symptoms from any of these six socio-economic strata are, however, extremely likely to report to clinics and hospitals and receive appropriate clinical and haematological assessment and therapy [15].

Conclusions
Co-infections of DENV and SARS-CoV-2 had notably heightened incidences of WHO 1997 DHF/DSS, WHO 2009 SD and SD warning sign criteria.Importantly, individuals who were previously infected with SARS-CoV-2 before DENV infections exhibited significantly increased incidences of thrombocytopenia (as per DHF/DSS criteria) as well as several SD warning signs.These findings underscore the critical importance for healthcare professionals to further evaluate the incidence of DENV-SARS-CoV-2 co-infections and question DENV-infected patients about their previous incidence of SARS-CoV-2 infections and apply both the WHO 1997 and 2009 DHF/DSS/SD and SD warning sign criteria to design and provide optimal treatment.Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/pathogens13070573/s1,Table S1: Clinical Chracteristics of the Non-severe (DF) or Severe (DHF/DSS/SD) DENV-infected Patients; Table S2: DENV-infected Patients' Laboratory Results from Non-severe (DF) and Severe (DHF/DSS/SD) cases; Table S3: Clinical characteristics of IgMcapture ELISA-confirmed DENV infected patients with or without Previously-Confirmed SARS-CoV-2 infections; Table S4: Collinearity analysis in the multiple logistic regression co-infection model; Table S5

Figure 1 .
Figure 1.Identification of the important features of DHF/DSS/SD in patients using the random forest model.The OOB error rate is 14.5% with the number of trees (ntrees) (500) and 6 nodes tested (mtry).

Figure 1 .
Figure 1.Identification of the important features of DHF/DSS/SD in patients using the random forest model.The OOB error rate is 14.5% with the number of trees (ntrees) (500) and 6 nodes tested (mtry).

Table 1 .
General characteristics and clinical features of the study population who had confirmed DENV infections before the COVID-19 pandemic (2018-2019) compared to during the COVID-19 pandemic (2020-2022).

Table 2 .
Demographic and clinical features of confirmed DENV-SARS-CoV-2 co-infections and non-coinfected cases.

Table 3 .
Clinical characteristics of DENV-infected patients associated with SARS-CoV-2 co-infection using logistic regression analysis.

Table 4 .
Clinical characteristics associated with DHF/DSS/SD or SD warning signs using logistic regression analysis.

Table 4 .
Clinical characteristics associated with DHF/DSS/SD or SD warning signs using logistic regression analysis.
: Collinearity Analysis Results of the Multiple Logistic Regression Age-adjusted Co-infection Model; Table S6: Random Forest (RF), Decision Tree (DT) Performance during the Training and Testing Stages; Table S7.Clinical Symptoms of DENV infected Patients with Previously Confirmed SARS-CoV-2 infections; Table S8: Collinearity Analysis in the Multiple Logistic Regression of DENV Infected Patients with Previous SARS-CoV-2 Infections.